Tunable asymmetric reflectance in silver films near the percolation threshold

We report on the optical characterization of semicontinuous nanostructured silver films exhibiting tunable optical reflectance asymmetries. The films are obtained using a multi-step process, where a nanocrystalline silver film is first chemically deposited on a glass substrate and then subsequently coated with additional silver via thermal vacuum-deposition. The resulting films exhibit reflectance asymmetries whose dispersions may be tuned both in sign and in magnitude, as well as a universal, tunable spectral crossover point. We obtain a correlation between the optical response and charge transport in these films, with the spectral crossover point indicating the onset of charge percolation. Such broadband, dispersion-tunable asymmetric reflectors may find uses in future light-harvesting systems.Comment: 18 pages, 5 figures, accepted by Journal of Applied Physic

Quantitative Assessment of Blood Pressure Measurement Accuracy and Variability from Visual Auscultation Method by Observers without Receiving Medical Training

This study aimed to quantify blood pressure (BP) measurement accuracy and variability with determinations from visualizing Korotkoff sound waveform. Thirty video clips of BP recordings from the educational training database of the British Hypertension Society were converted to Korotkoff sound waveforms. Ten observers without receiving medical training were asked to determine systolic and diastolic BPs (SBP and DBP) from the randomly arranged video clips and Korotkoff sound waveforms using two measurement methods: a) traditional manual auscultatory method of listening for Korotkoff sounds; and b) visual auscultation method by visualising the Korotkoff sound waveform, which was repeated three times on different days, making a total of 6 BP measurements from each observer on each BP recording. The measurement variability was calculated from the standard deviation of the three repeats, and the measurement error was calculated against the reference answers. Statistical analysis showed that, in comparison with the traditional manual auscultatory method, visual auscultation method significantly reduced overall measurement variability from 2.2 to 1.1 mmHg for SBP and from 1.9 to 0.9 mmHg for DBP (both p<0.001). It also showed that BP measurement errors were significant for both techniques (all p<0.01, except DBP from the traditional method). Although significant, the overall mean measurement errors were small, which were -1.5 and -1.2 mmHg for SBP, and -0.7 and 2.6 mmHg for DBP, respectively from the traditional manual auscultatory and visual auscultation methods. In conclusion, the visual auscultation method had the ability to achieve an acceptable degree of BP measurement accuracy, with smaller measurement variability in comparison with the traditional manual auscultatory method

Significantly Reduced Blood Pressure Measurement Variability for Both Normotensive and Hypertensive Subjects: Effect of Polynomial Curve Fitting of Oscillometric Pulses

This study aimed to compare within-subject blood pressure (BP) variabilities from different measurement techniques. Cuff pressures from three repeated BP measurements were obtained from 30 normotensive and 30 hypertensive subjects. Automatic BPs were determined from the pulses with normalised peak amplitude larger than a threshold (0.5 for SBP, 0.7 for DBP, and 1.0 for MAP). They were also determined from cuff pressures associated with the above thresholds on a fitted curve polynomial curve of the oscillometric pulse peaks. Finally, the standard deviation (SD) of three repeats and its coefficient of variability (CV) were compared between the two automatic techniques. For the normotensive group, polynomial curve fitting significantly reduced SD of repeats from 3.6 to 2.5 mmHg for SBP and from 3.7 to 2.1 mmHg for MAP and reduced CV from 3.0% to 2.2% for SBP and from 4.3% to 2.4% for MAP (all P<0.01). For the hypertensive group, SD of repeats decreased from 6.5 to 5.5 mmHg for SBP and from 6.7 to 4.2 mmHg for MAP, and CV decreased from 4.2% to 3.6% for SBP and from 5.8% to 3.8% for MAP (all P<0.05). In conclusion, polynomial curve fitting of oscillometric pulses had the ability to reduce automatic BP measurement variability

SYSTEM INCLUDING CONOSCOPE LENS FOR MEASURING POLARIZATION CHARACTERISTICS OF WIDE FIELD-OF-VIEW LENSES

A lens measurement system including 1) a light source, 2) a lens mounting support configured to hold a lens so that light emitted by the light source is incident on the lens, 3) a conoscope lens positioned to receive light refracted by the lens, and 4) a polarization camera positioned to receive light emitted from the conoscope lens

Vehicle Communication using Secrecy Capacity

We address secure vehicle communication using secrecy capacity. In particular, we research the relationship between secrecy capacity and various types of parameters that determine secrecy capacity in the vehicular wireless network. For example, we examine the relationship between vehicle speed and secrecy capacity, the relationship between the response time and secrecy capacity of an autonomous vehicle, and the relationship between transmission power and secrecy capacity. In particular, the autonomous vehicle has set the system modeling on the assumption that the speed of the vehicle is related to the safety distance. We propose new vehicle communication to maintain a certain level of secrecy capacity according to various parameters. As a result, we can expect safer communication security of autonomous vehicles in 5G communications.Comment: 17 Pages, 12 Figure

Segmentation of kidney lesions with attention model based on Deeplab

We participate this challenge by developing a hierarchical framework. We build the model from two fully convolutional networks: (1) a simple Unet model to normalize the input iamges, (2) a segmentaion network which is an attention model based on Deeplab model. Two models are connected in tandem and trained end-to-end. To ensure a better results, we use the preprocess method proposed by nnUnet in our experiments

Label Mask AutoEncoder(L-MAE): A Pure Transformer Method to Augment Semantic Segmentation Datasets

Semantic segmentation models based on the conventional neural network can achieve remarkable performance in such tasks, while the dataset is crucial to the training model process. Significant progress in expanding datasets has been made in semi-supervised semantic segmentation recently. However, completing the pixel-level information remains challenging due to possible missing in a label. Inspired by Mask AutoEncoder, we present a simple yet effective Pixel-Level completion method, Label Mask AutoEncoder(L-MAE), that fully uses the existing information in the label to predict results. The proposed model adopts the fusion strategy that stacks the label and the corresponding image, namely Fuse Map. Moreover, since some of the image information is lost when masking the Fuse Map, direct reconstruction may lead to poor performance. Our proposed Image Patch Supplement algorithm can supplement the missing information, as the experiment shows, an average of 4.1% mIoU can be improved. The Pascal VOC2012 dataset (224 crop size, 20 classes) and the Cityscape dataset (448 crop size, 19 classes) are used in the comparative experiments. With the Mask Ratio setting to 50%, in terms of the prediction region, the proposed model achieves 91.0% and 86.4% of mIoU on Pascal VOC 2012 and Cityscape, respectively, outperforming other current supervised semantic segmentation models. Our code and models are available at https://github.com/jjrccop/Label-Mask-Auto-Encoder

Exploring the shared genes of hypertension, diabetes and hyperlipidemia based on microarray

Given their relationship with metabolic syndrome and systematic inflammatory diseases, the pathogenesis of hypertension, hyperglycemia, and hyperlipidemia is closely related. To explore the common genes among these three conditions, spontaneous hypertensive rats (SHR), spontaneous diabetic Goto-Kakizaki rats (GK) and hyperlipidemia rats (HMR) were reared for experiments. Gene array was used to identify the genes of SHR, GK and HMR compared with normal Wistar rats using TBtools software. First, real-time PCR was applied to verify these genes, and Cytoscape software was used to construct networks based on the National Center for Biotechnology Information (NCBI) database. Second, Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis was performed to classify the genes. Visualization and Integrated Discovery (DAVID) database and Gene Ontology database were used to explore the biological function. Finally, Onto-tools Pathway Express was used to analyze the pathways of shared genes. Importantly, upregulated common genes, such as Bad, Orm1, Arntl and Zbtb7a, were used to construct a network of 150 genes, while downregulated genes, such as Mif and Gpx1, formed a network of 29 genes. Interestingly, the networks were involved in various pathways, such as insulin signal pathway, endometrial cancer pathway, circadian rhythm pathway, and pancreatic cancer pathway. We discovered common genes of SHR, GK and HMR compared with normal Wistar rats, and the association of these genes together with biological function were preliminarily revealed